Smart antenna, method and apparatus for adaptive beam forming

ABSTRACT

The present invention discloses a beam forming method for a smart antenna and a beam forming apparatus for a smart antenna. Said method comprises: implementing pre-multibeam processing and time delay aligning to array signals; calculating a suboptimum weight by means of a pilot frequency symbol; iteratively calculating an optimum weight with said suboptimum weight as an initial value; forming beams by means of said optimum weight. To use the beam forming method and apparatus of the present invention, it can reduce the bit error ratio for receiving and outputting greatly and avoid the multiplication between large matrixes and matrix inversion and then replace them by simple addition and multiplication, so as to reduce the difficulty for hardware implement and make it easier to be performed.

FIELD OF THE INVENTION

The present invention relates to radio communication field, moreparticularly, to a technique for the adaptive beam forming of a smartantenna.

BACKGROUND OF THE INVENTION

With the rapid development of modern digital signal processingtechnology in recent years, continuously the processing capability of aDSP chip is enhanced and the price of the chip is reduced, so that it ispossible to form antenna beams at baseband with digital technology,therefore the smart antenna technology with a key technology of anadaptive beam forming algorithm is widely used in CDMA communication.

In a CDMA communication system, accurate time delay information isrequired before the adaptive beam forming of a smart antenna, otherwisethe result of adaptive processing will be influenced seriously due tothe correlation of codes. At present, there are many beam formingalgorithms for smart antennas, but the common disadvantage of themconsists in that it does not solve the problem of multipath time delay.It is supposed that the time delay information is known accurately orthat the time delay is known in existing adaptive beam formingalgorithms for smart antennas, and this kind of algorithms relate alittle detailed embodiments and structures. In the Chinese patentapplication with a publication number of 1235391, named “Adaptive ArrayAntenna Optimizing and Forming Beams in Advance for Code DivisionMultiple Access System”, the calculation of the weight in complex numberis divided into two parts, i.e. initial weight designing and operationalweight processing, since this application does not solve the problem oftime delay accuracy and it requires a high initial weight, theperformance of the smart antenna is hardly ensured. Because it iscrucial for an adaptive beam forming method to determine the multipathtime delay accurately, how to search out the time delay informationaccurately is a problem which should be solved by the prior artsurgently.

SUMMARY OF THE INVENTION

According to one aspect of the present invention, it provides a beamforming method for a smart antenna, which comprises the steps ofimplementing pre-multibeam processing and time delay aligning to arraysignals; calculating a suboptimum weight by means of a pilot frequencysymbol; iteratively calculating an optimum weight with said suboptimumweight as an initial value; forming beams by means of said optimumweight.

According to another aspect of the present invention, it provides a beamforming apparatus for a smart antenna, and the apparatus comprises: aspace domain forming module for implementing beam forming to the signalsreceived by an antenna array, and said space domain forming modulefurther comprises a pre-multibeam time delay searching unit forimplementing pre-multibeam processing and time delay aligning to arraysignals; a time domain processing module for obtaining the transmitteddata based on the signals beam-formed by said space domain formingmodule; and a re-spreading and iterating module for generating areference signal basing on the data information acquired by said timedomain matched filtering module, calculating an iteration error andfeeding it back to said space domain beam forming module.

According to another aspect of the present invention, it provides asmart antenna, which comprises the beam forming apparatus mentionedabove and an antenna array composed by a number of elements.

BRIEF DESCRIPTION OF THE DRAWINGS

The above-mentioned or other advantages, objects and features of thepresent will be clearer by describing the preferred embodiments of theinvention with reference to the drawings.

FIG. 1 is an orientation diagram of the four narrow beams of a coversector generated by the pre-multibeam processing according to anembodiment of the present invention;

FIG. 2A is a flow chart showing the beam forming method according to apreferred embodiment of the present invention;

FIG. 2B is a detailed flow chart showing the iteration calculation ofthe weight in the embodiment shown in FIG. 2;

FIG. 3 is a block diagram showing the construction of the smart antennaaccording to a preferred embodiment of the present invention;

FIG. 4 is a curve showing the contraction between the outputsignal-to-noise ratios of the structure with the pre-multibeamprocessing and of the structure without the pre-multibeam processing ofthe present invention;

FIG. 5 is a curve showing the contraction between the output bit errorrates of the structure with the pre-multibeam processing and of thestructure without the pre-multibeam processing of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

An embodiment of the present invention will now be described withreference to the drawings.

FIG. 1 is a beam orientation diagram, in which shown that four beams canmagnificently cover a sector of 120° in a range of −60°˜60°, and theside lobes are low.

FIG. 2A is a flow chart showing the beam forming method according to apreferred embodiment of the present invention. As shown in FIG. 2A, inStep 101 firstly, in order to obtain the accurate time delays ofrespective multipathes before the adaptive beam forming, so as to ensurethe beam forming of the smart antenna to be more reliable, the receivedarrays are implemented pre-multibeam processing in parallelsimultaneously during the process of calculating the adaptive weight tosupply an array received signal with aligned time delays to the adaptiveweight calculation in real time.

More particularly, the processing includes generating a number of fixednarrow beams covering the sector, for example, in an embodiment, saidsector is of 120° and four fixed narrow beams are generated herein (asshown in FIG. 1). The beam with maximal energy value can be found byimplementing beam forming to the data received by the array andimplementing time delay searching to the generated beam domain signalusing said fixed narrow beams, and the time delay value in this beam isthe time delay value of the array received signal. The data received bythe arrays is implementing time delay aligning based on this time delayvalue and the array received vector of the information bits after thetime delay aligning is represented by X.

In different embodiments of the present invention, all the directions ofarrival of mobile stations in the sector can be contained within thepre-multibeam by adjusting the size of the sector and the coverage areaaccording to requirements. The number of the beams and the beam widthcan also be adjusted according to requirements. If the direction ofarrival of a mobile station lies between two beams exactly, these twobeams can be incorporated into one wide beam to ensure effective beamcoverage.

The pre-multibeam processing of the present invention can supplyaccurate time delay information to the adaptive calculation method ofthe smart antenna, and further ensure the accuracy and the reliabilityof the adaptive algorithm, and it is proved via experiments that thecombination of the pre-multibeam processing and the adaptive algorithmin the present invention improves the signal-to-noise ratio of thereceived signals of the smart antenna greatly and achieves the superiorperformance of the smart antenna well, compared to the result of thesimple adaptive algorithm without the pre-multibeam processing.

In Step 102 subsequently, the suboptimum weight is calculated. Duringall the pilot frequency bits of the first interval of the current frame,a known pilot frequency symbol is regarded as a reference signal, and acorrelation matrix is calculated based on the reference signal afterperforming spread spectrum and scramble and the array received vectorsafter aligning the time delays, and then the matrix serves as thesuboptimum weight. Wherein, the signal after re-spreading and scramblingduring the pilot frequency bits is r=b_(pilot)·CS, and the suboptimumweight is W=E[Xr*], wherein, b_(pilot) is the known pilot frequencysymbol, CS is the resulted sequence of the multiplication between spreadfrequency codes and scramble codes. In this Step, a known pilotfrequency bit is regarded as a reference signal, and the optimum weightis calculated based on the reference signal after performing spreadingand scrambling and the array received vectors after the time delayaligning, and then the optimum weight serves as the initial value forpost minimum mean square error iteration, since this initial value iscloser to the ideal weight, the convergence rate will be improvedgreatly (It will be converged after 3-4 symbol bits sometimes), whichmeets the requirement for the real time processing of a communicationsystem.

Then in Step 103, the suboptimum weight is regarded as an initial valueand the weight is calculated iteratively. This Step will now bedescribed in detail with reference to FIG. 2B.

FIG. 2B is a detailed flow chart showing the iteration calculation ofthe weight in the embodiment shown in FIG. 2. As shown in FIG. 2B,firstly in Step 110, beams are formed with an initial weight, and itsupposes that the signal after the beam forming is Y, then Y=W×X,wherein W is a weight.

Next in Step 111, the signal after the beam forming is de-spread anddescrambled,${{v(j)} = {{Imag}\left( {\sum\limits_{k = {1 + {jK}}}^{{({j + 1})}K}{{y(k)}{c(k)}}} \right)}},$wherein j represents the j^(th) information symbol, K represents aspread factor, Imag( ) represents to calculate the imaginary part.

In Step 112, a complex gain of the l^(th) piece of multipathincorporated by RAKE is estimated based on the result of thede-spreading and the descrambling with the pilot frequency section,${{G_{c}(l)} = {\frac{1}{q}{\sum\limits_{m = 1}^{q}\left\lbrack {b_{m} \cdot {v(m)}} \right\rbrack}}},$wherein q is the number of pilot frequency bits, and b_(m) is a knownpilot frequency bit.

In Step 113, the transmitted control information is determined,b=sign(Im ag(v)G_(c)*(l)).

In Step 113, the determined control information is spread, d=b·C andthen the control information is descrambled, r =d×S, it should be notedthat if it is during a pilot frequency bit, a known pilot frequency bitb=b_(pilot) can be used to calculate r directly (without Step 113). Thusthe reference signal r is obtained.

In Step 115, the iteration error is calculated, E=r−Y, r is thereference signal calculated before, Y is the signal of the up-to-datebeam forming.

In Step 116, a new weight is calculated by a iteration formula:W_(i+1)=W_(i)+μ·X×E^(H), wherein, W_(i) is the weight calculated by laststep or by the iteration; μ is the step length of the iteration, whichcan be 0.1 or 0.01; E is the error matrix calculated before, E^(H) isits conjugate transpose.

Then in Step 117, the newly calculated weight is regards as an initialweight, and it turns back to Step 110.

In one embodiment of the present invention, the iterative calculationmentioned above is implemented at each interval of one frame. In otherpreferred embodiments, under the condition that the accuracy requirementcan be achieved, the signal data of the corresponding interval isprocessed smartly by taking the optimum weight for the first interval inthe frame obtained through the above-mentioned method as the optimumweight for all the intervals in the frame, or taking the optimum weightfor one random interval in the frame as the optimum weight for thelatter intervals, which can further reduce the calculation amount of theweight iteration.

Back to FIG. 2A now, after the iterative calculation of weight (Step103), said process comes to Step 104, in which the iteration error isdetermined whether to meet the requirement. According to one embodimentof the present invention, the determination can be accomplished bydetermining whether the mean square value of the error to be within apredetermined threshold. If the requirement can not be achieved, Step102, 103 will be repeated until the mean square deviation is within thepredetermined threshold. If the requirement can be achieved, it goesforward to Step 105, then the new weight is saved as the optimum weightof the interval, and it will be used to perform the beam forming of thereceived signal, descramble and de-spread the I channel data of theuplink channel, accomplish the information receiving and account theoutput signal-to-noise ratio.

It can be seen from above description that the beam forming method of asmart antenna according to the embodiment of the present inventionavoids the multiplication between large matrixes and matrix inversionand replaces them by simple addition and multiplication by adoptingminimum mean square error iteration, so as to reduce the difficulty forhardware implement and make it easier to be performed.

FIG. 3 is a block diagram showing the construction of the smart antennaaccording to a preferred embodiment of the present invention. As shownin FIG. 3, the smart antenna according to the embodiment comprises: anantenna array composed by a number of elements (1-M), a space domainforming module 21, a time domain processing module 22 and a re-spreadingand iterating module 23. Each said antenna element (1-M) respectivelycomprises its antenna front end (not shown in the FIG. ) for receivingradio signals and converting them into received signals X=[x₁, x₂, . . .x_(M)], which is known by those skilled in the art.

At same time, the space domain forming module 21, the time domainprocessing module 22 and the re-spreading and iterating module 23 alsocompose the beam forming apparatus for a smart antenna according to theembodiment of the present invention. The smart antenna and its beamforming apparatus according to the embodiment of the present inventionwill now be described in detail with reference to the drawings.

The space domain forming module 21 is connected to each element of theantenna array (1-M), so as to implement space domain processing and beamforming to the received signal X=[x₁,x₂, . . . x_(M)] of the antennaarray. The space domain forming module 21 comprises: pre-multibeam timedelay searching units 215.1-215.M, each of which is connected to anantenna element respectively, a weight updating unit 213, multipliers211.1-211.M and an adder 212.

The pre-multibeam time delay searching unit 215 generates several fixednarrow beams (as shown in FIG. 1) , and forms array received signalsusing these beams respectively to obtain beam signals, during theoperation period. Then it implements time delay searching to the beamsignals, selects the beam with the highest energy value, records thetime delay value of this beam as the path time delay of the arrayreceived signals, and implements time delay aligning to the arrayreceived signals.

After the time delay aligning, the aligned array received signals aretransmitted to the corresponding multiplier (211.1-211.M), respectively.These multipliers perform their multiply operations respectively basedon the corresponding weights w₁,w₂ , . . . , w_(M) provided by theweight updating unit 213. The results of these multiply operations aresummed in the adder 212 and output to the time domain processing module22 as the result of beam forming.

The weight updating unit 213 calculates weights iteratively by means ofthe minimum mean square error rule and based on the error informationsent from the re-spreading and iterating module 23 or the signal spreadand scrambled during the pilot frequency bits of the first intervalwhich services as the reference signal for calculating the suboptimumweight, then the unit assigns the calculated weights to thecorresponding multipliers (211.2-211.M).

The time domain processing module 22 comprises: a descrambler 221, ade-spreader 222, a channel estimating and compensating RAKE unit (223,224) and a determiner 225. The descrambler 221 and the de-spreader 222are used to descramble and de-spread the signal which has beenimplemented the beam forming. The channel estimating and compensatingRAKE unit 223 is used to process the descrambled data, to reduce theinfluence due to channels and to implement RAKE incorporating to thesignals of multiple paths. And the determiner 225 is used to determinethe data bits to be output from the signal after the RAKE incorporating.

The re-spreading and iterating module 23 mainly comprises: a re-spreader231, a scrambler 232 and an iteration error computing unit 233. There-spreader 231 and the scrambler 232 re-spread and scramble thedetermined data output from the time domain processing module 22, so asto generate an iteration reference signal r. The iteration errorcomputing unit 233 then calculates an iteration error E based on thecalculated iteration reference signal and the received signal Y isbeam-formed by the space domain forming module 21. The iteration errorcomputing unit 233 further transmits the iteration error E to the weightupdating unit 213 of the space domain forming module 21. In addition,the re-spreading and iterating module 23 further comprises a unit 234for spreading and scrambling the pilot frequency bits of the firstinterval and a unit 235 for spreading and scrambling the pilot frequencybits of the other intervals as reference signals.

The operation of the beam forming apparatus according to this embodimentof the present invention will now be described.

First of all, the time delay information is searched by thepre-multibeam time delay searching unit 215 and then the array receivedsignals are implemented time delay aligning so as to be basebandreceived signals [X₁-X_(M)]. Next, the baseband signals will beprocessed.

During all the pilot frequency bits of the first interval, the signalsprovided by the unit 234 which are spread and scrambled during the knownpilot frequency bits and service as reference signals, together with thebaseband signals [X₁-X_(M)] which have been implemented time delayaligned are used to calculated a cross correlation matrix, so as tocalculate the suboptimum weight until the pilot frequency bits of thefirst interval end. The suboptimum weight at the time when the pilotfrequency bits of the first interval end is input to the adder 211, andthe beam forming signals of each element are incorporated into onesignal by the adder 212.

Then the signal will be divided into two signals, the one is input tothe iteration error computing module 233 of the re-spreading anditerating module 23 as the minuend vector for the error computing, theother is input to the descrambler 221 of the time domain processingmodule 22. The Q channel data of the descrambled data then enters thede-spreader 222; as a result, the de-spread data has the unit of bit andcan be processed by the channel estimating and compensating RAKE unit223, 224 to reduce the influence due to the channels.

The data processed by the determiner 225 are symbol bits of 1, −1 . . ., and input to the re-spreading and iterating module 23. When thecurrent moment is within the information bits, the symbol bits inputfrom the time domain processing module 22 are input to the iterationerror computing module 233 via the re-spreader 231 and the scrambler232, and then minus the signal previously input from the adder 212 toobtain an error signal which will be input to the weight updating module213 of the space domain beam forming module 21. When the current momentis within the pilot frequency bits of other intervals, the re-spread andscrambled signal of a known pilot frequency bit provided by the unit 235serves as one input of the iteration error computing module 233 andminuses the signal previously input from the adder 212 to obtain anerror signal which will be input to the weight updating module 213 ofthe space domain beam forming module 21.

The reference signal input to the weight updating unit 213 and thealigned received signals [X₁-X_(M)] are iterated based on the minimummean square error rule to calculate the optimum weight. In detail, aniteration formula is adopted: W_(i+1)=W_(i)+μ·X×E^(H), wherein, W_(i) isthe weight calculated or iterated in last step; μ is the step length ofthe iteration ; E is the error calculated by the iteration errorcomputing module 233; and E^(H) is the conjugate transpose of E.

If the iteration error which has been implemented beam forming with thisweight (the error is calculated by the iteration error computing module233) meets requirement, the data of the beam forming will be implementeddescrambling, de-spreading, channel estimating and compensating and RAKEincorporating, and then it will be output.

All the components composing the beam forming apparatus of the smartantenna according to the embodiment of the present invention can behardware modules or software modules, and these modules can beintegrated into a specific chip or FPGA, also part of them can beimplemented by software in DSP.

FIG. 4 is a curve showing the simulation contraction between the outputsignal-to-noise ratios before and after the adaptive beam algorithm ofthe present invention performing the pre-multibeam. The abscissa in FIG.4 represents the input signal-to-noise ratio, Eb/N0 , with a variationrange of 4-12 dB. The ordinate represents the output signal-to-noiseratio. Both the interval units of the abscissa and the ordinate are 2dB. The simulation is under the conditions of a macrocell with 20 users,a data length of 20 frames and a symbol rate of 60 kbps, in this figure,“NO Beam” represents the adaptive beam forming method withoutpre-multibeam processing of the prior art, and “Beam+Algorithm”represents the adaptive beam forming method of the present invention,which uses the pre-multibeam and the de-spreading and re-spreadingmulti-objective array assisted by pilot frequency bits and based on theminimum mean square error rule. V represents the moving speed, with aunit of kmph. As shown in the figure, when the input signal-to-noiseratio is 4 dB and the speed of the mobile station is 30 kmph, the outputsignal-to-noise ratio obtained through the present invention is close to13 dB, while the output signal-to-noise ratio obtained through themethod without pre-multibeam processing is about 5.8 dB, and thedifference between them is about 7.2 dB, likewise, when the inputsignal-to-noise ratio is 6, 8, 10 and 12 dB, it has similar results, sothe method of the present invention improves the output signal-to-noiseratio greatly, compared to the adaptive method without pre-multibeamprocessing of the prior art.

The solid lines and the dashed lines in FIG. 5 represent the bit errorrates of the signals received through the methods and the structures ofthe prior art and the present invention respectively. Similarly, it canbe seen from FIG. 5 that the output bit error rate will be reducedgreatly by using the method and the structure of the present invention,compared to the prior art.

Although the present invention is described in detail with some exampleembodiments of the present invention hereinbefore, the embodimentsmentioned above are not exhaustive, and various advantages andmodifications may be achieved without departing from the spirit or scopeof the present invention by those skilled in the art. For example,although the embodiments mentioned above are aimed to WCDMA systems,those skilled in the art should understand that they are also suitablefor other systems which are on the basis of CDMA. Accordingly, theinvention is not limited to the specific details and representativeembodiments shown and described herein, and the scope of the presentinvention is only defined by the appended claims.

1. A beam forming method for a smart antenna, which comprises:implementing pre-multibeam processing and time delay aligning to arraysignals; calculating a suboptimum weight by means of a pilot frequencysymbol; iteratively calculating an optimum weight by means of saidsuboptimum weight as an initial value; forming a beam by means of saidoptimum weight.
 2. The beam forming method for a smart antenna accordingto claim 1, wherein, said step of implementing pre-multibeam processingto array signals comprises: generating a number of fixed beams coveringa sector, and implementing beam forming to the data received by anarray, by means of said fixed beams; implementing beam time delaysearching to the generated beam domain signals, selecting the maximumbeam of each multiple paths, and aligning the array data by means of thetime delay value of this beam.
 3. The beam forming method for a smartantenna according to claim 2, wherein, the coverage area of the beam andthe amount and the width of the beam can be adjusted with the size ofthe sector to ensure all the directions of arrival of the mobilestations in the sector are included within said pre-multibeam.
 4. Thebeam forming method for a smart antenna according to claim 1, wherein,said step of calculating the suboptimum weight comprises: spreading andscrambling the known pilot frequency bits of the first interval of acurrent frame, as a reference signal; based on the minimum mean squareerror rule, calculating the approximate solution of the correlationmatrix of said reference signal and the array received signals aftertime delay aligning, as the suboptimum weight.
 5. The beam formingmethod for a smart antenna according to claim 1, wherein, said step ofiteratively calculating the optimum weight comprises: forming beams forthe array received signals after time delay aligning, by means of theinitial weight; implementing descrambling and de-spreading to thereceived signals after beam forming, and determining controlinformation; re-spreading and scrambling the determined controlinformation, as an iteration reference signal; calculating iterationerror by means of the iteration reference signal and the receivedsignals after beam forming; calculating a new weight; iterating based onthe new weight as the initial weight.
 6. The beam forming method for asmart antenna according to claim 5, wherein, when calculating the newweight, an iteration formula W_(i+1)=W_(i)+μ·X×E^(H) is used, wherein,W_(i) is the weight calculated by last iteration, μ is the step lengthof the iteration, E is the iteration error, E^(H) is its conjugatetranspose, r is the iteration reference signal, Y is the receivedsignals after beam forming.
 7. The beam forming method for a smartantenna according to claim 5, wherein, in said step of determining, theinformation of a known pilot frequency bit serves as the determinedoutput during the pilot frequency bit.
 8. The beam forming method for asmart antenna according to claim 5, wherein, before the step of formingbeams by means of said optimum weight, said method further comprises:determining whether the iteration error meets requirement; if theiteration error does not meet requirement, repeating said step ofcalculating the suboptimum weight and said step of iterativelycalculating the optimum weight.
 9. The beam forming method for a smartantenna according to claim 8, wherein, said step of determiningcomprises: calculating the mean square value of the iteration error, ifthe calculated mean square value of the iteration error is larger than apredetermined threshold, determining that the iteration error does notmeet requirement, otherwise determining that the iteration error meetsrequirement.
 10. The beam forming method for a smart antenna accordingto claim 8, wherein, the optimum weight obtained in the first intervalof each frame serves as the optimum weight of the whole frame to processthe signals of all the intervals of the frame.
 11. A beam formingapparatus for a smart antenna, which comprises: a space domain formingmodule for implementing beam forming to the signals received by anantenna array, and said space domain forming module further comprises apre-multibeam time delay searching unit for implementing pre-multibeamprocessing and time delay aligning to array signals; a time domainprocessing module for obtaining the transmitted data based on thesignals beam-formed by said space domain forming module; and are-spreading and iterating module for generating a reference signalbased on the data information acquired by said time domain matchedfiltering module, calculating the iteration error and feeding it back tosaid space domain beam forming module.
 12. The beam forming apparatusaccording to claim 11, wherein, said space domain forming module furthercomprises: a weight updating unit for calculating weights used for beamforming by means of the iteration error fed back from the re-spreadingand iterating module; multipliers for multiplying the correspondingweights calculated the weight updating unit and the received signals ofthe elements of the corresponding antenna array; and an adder for addingthe output of the multipliers.
 13. The beam forming apparatus accordingto claim 11, wherein, said time domain processing module comprises: adescrambling and de-spreading unit for descrambling and de-spreading thesignals beam-formed by the space domain forming module; a RAKEincorporating unit for incorporating the signals of multiple paths; anda determiner for determining the data to be transmitted from the signalsafter the RAKE incorporating.
 14. The beam forming apparatus accordingto claim 11, wherein said re-spreading and iterating module comprises: are-spreading and scrambling unit for re-spreading and scrambling thetransmitted data obtained by said time domain processing module, as aniteration reference signal; an iteration error computing unit forcalculating the iteration error based on the iteration reference signalfrom said re-spreading and scrambling unit and the received signalsbeam-formed by said space domain forming module.
 15. The beam formingapparatus according to claim 14, wherein, said weight updating unit ofthe space domain forming module iteratively calculates an optimum weightby means of the iteration error calculated by the iteration errorcomputing unit.
 16. The beam forming apparatus according to claim 15,wherein, said weight updating unit of the space domain forming modulecalculates the cross correlation matrix of the spreading and scramblingsignals of the known pilot frequency bit and the received pilotfrequency range signals, based on the minimum mean square error rule toobtain a suboptimum weight, as the initial value of iterationcalculating.
 17. The beam forming apparatus according to claim 16,wherein, said weight updating unit re-calculates the suboptimum weightwhen it is determined that said iteration error does not meetrequirement.
 18. The beam forming apparatus according to claim 14,wherein, said iteration error computing unit regards the signal spreadand scrambled by means of a known pilot frequency bit as the iterationreference signal during pilot frequency bits.
 19. A smart antenna, whichcomprises an antenna array composed by elements and the beam formingapparatus of claim 11.